Data Scientist

Battery Market Context

In 2019, global battery production could power 5 million EVs, however the equivalent of 1 i n every 6 batteries were scrapped in production. That's $4 Billion of waste i n 2019, due largely to insufficient data and analytics in production. Batteries are fundamental to our clean energy transition, but unless we change the status quo, their cost will remain a major barrier.

About Feasible, Inc.

Our mission is to accelerate the clean energy transition by decreasing the cost of battery manufacturing.  We are pioneers in advanced process inspection & intelligence solutions, enabling our customers to "See Batteries Differently."  Our EchoStat platform uses ultrasound and data analytics to deliver unique,valuable insights that create value in battery production by speeding up time-to-market for new batteries, accelerating yield ramp for new production processes, and improving steady-state productivity.

Founded i n 2016, Feasible is headquartered in Emeryville, CA. Since inception, Feasible has received over $8M in grants and equity funding from Chrysalix Ventures, Incite Labs, NSF, DOE (ARPA-e), Elemental Excelerator, Activate (formerly Cyclotron Road), and others. We are currently working with leading battery manufacturers and automakers to test and evaluate our beta systems.

Our Culture and Values

􀆔 We are dedicated to building a world-class company that will improve the world.

􀆔 We work closely on a foundation of mutual trust and data-driven decisions.

􀆔 We value personal growth, continuous learning, safety, and inclusion.

􀆔 We believe the most innovative teams seek out, welcome and celebrate all forms of diversity.

Role

As a data scientist at Feasible you will join a small, nimble team of engineers creating cutting-edge battery inspection equipment. You will be an integral part of analyzing the data produced with this equipment, developing a deeper understanding of the data's relationship to the battery's production history and performance, and creating tools and techniques to achieve those goals.

On a typical day, you may: perform investigative analysis on experimental data; design and implement algorithms for distilling ultrasonic signals into meaningful features, and correlate those features with performance data; build analytics tools and visuali􀁝ations to empower our engineers and customers; optimize, automate, and streamline our analytics pipeline, and integrate the pipeline with real-time data streams; or communicate your work to stakeholders with varied backgrounds.

You value careful listening, thoughtful questions, and data-driven discussions. You are comfortable with gathering and distilling information to drive the direction of open-ended projects.

The ideal candidate will approach this work with a mixture of intellectual curiosity, thoughtful creativity, and methodical rigor. The ideal candidate gets great satisfaction from seeing people do great things with their work, and above all is excited to solve hard problems that have a positive impact on the world's clean energy future.

Responsibilities

􀆔 Build predictive models blending acoustic and electrochemical data

􀆔 Feature engineering

􀆔 Build out data pipelines

􀆔 Build out data visuali􀁝ation tools

􀆔 Develop innovative analysis techniques

􀆔 Analyze data from customers 

Requirements

􀆔 Practical experience working with and comparing large datasets acquired from experiments

􀆔 Python (Numpy, Scipy, Pandas, Scikit-learn)

􀆔 Experience with predictive modeling (Classification, Clustering, Dimensionality Reduction)

􀆔 SQL Database proficiency (primarily through queries)

􀆔 Statistics

􀆔 Data visualization

Nice to haves (bonus skills)

􀆔 Experience with frequency domain data

􀆔 Experience with time-series analysis

􀆔 Experience with battery data

􀆔 Physical i ntuition about data, or experience w/ real world data

Benefits

􀆔 Competitive compensation package.

􀆔 Medical, dental, vision, and life insurance.

􀆔 8 weeks of fully-paid parental leave.

􀆔 401(k).

􀆔 Flexible time-off policy.

Interested? Apply here: https://apply.workable.com/j/AD1FCE3AE4